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The Dynamics of Supply and Demand in mRNA Translation

Overview of attention for article published in PLoS Computational Biology, October 2011
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Title
The Dynamics of Supply and Demand in mRNA Translation
Published in
PLoS Computational Biology, October 2011
DOI 10.1371/journal.pcbi.1002203
Pubmed ID
Authors

Chris A. Brackley, M. Carmen Romano, Marco Thiel

Abstract

We study the elongation stage of mRNA translation in eukaryotes and find that, in contrast to the assumptions of previous models, both the supply and the demand for tRNA resources are important for determining elongation rates. We find that increasing the initiation rate of translation can lead to the depletion of some species of aa-tRNA, which in turn can lead to slow codons and queueing. Particularly striking "competition" effects are observed in simulations of multiple species of mRNA which are reliant on the same pool of tRNA resources. These simulations are based on a recent model of elongation which we use to study the translation of mRNA sequences from the Saccharomyces cerevisiae genome. This model includes the dynamics of the use and recharging of amino acid tRNA complexes, and we show via Monte Carlo simulation that this has a dramatic effect on the protein production behaviour of the system.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 89 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 2 2%
United Kingdom 2 2%
United States 2 2%
Argentina 1 1%
Israel 1 1%
Thailand 1 1%
China 1 1%
Unknown 79 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 26 29%
Student > Ph. D. Student 24 27%
Student > Bachelor 8 9%
Student > Master 7 8%
Professor 5 6%
Other 11 12%
Unknown 8 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 41 46%
Biochemistry, Genetics and Molecular Biology 16 18%
Physics and Astronomy 7 8%
Computer Science 5 6%
Engineering 3 3%
Other 8 9%
Unknown 9 10%